The rat genome sequence has been released to further the value of this widely used lab animal. Its genome can now be annotated systematically with respect to medically important functional aspects, including response to drugs (pharmacogenomics). To date, this has not been attempted for warfarin. Warfarin inhibits the vitamin K cycle and, thus, acts as a 'blood thinning'drug. It is one if the most widely used therapeutic drugs to alleviate health risks posed by blood clots, such as pulmonary embolisms, heart attacks and ischemic strokes. However, gene-drug interactions threaten the safe and effective application of warfarin in humans. Here, we annotate the rat genome with respect to genes that interact with warfarin and infer their human orthologs. First, Affymetrix microarrays are employed to detect induction or suppression of gene expression in response to warfarin in the liver (hepatic tissue). Second, bioinformatics will be used to identify genes in the rat genome that might interact with warfarin in silico. Third, the genetics of warfarin resistance in a German strain of rats is examined. All these three surveys will be assisted by genetic variation and association studies of candidate genes. Finally, results shall converge in a state-of-the-art bioinformatics analysis that infers genes, pathways, regulatory networks, and protein and regulatory sequence motifs interacting with warfarin in silico, thereby potentially extending results to other, extrahepatic tissues. Preliminary results reveal, among numerous others, a novel pathway involving a sulfotransferase that has plausible biochemical connections to the vitamin K cycle and for which a promoter polymorphism is significantly associated with warfarin response. Moreover, data show that the rat is a valid model for the human condition because the highly publicized warfarin-interacting genes Cyp2c9 and Vkorc1 emerged from preliminary analyses. However, novel sex-specific effects were observed. The study is first to identify the complement of genes, pathways, and regulatory networks that interact with warfarin in rat and infers their human counterparts. Results could assist predicting warfarin doses, side effects, and gene-drug interactions. Moreover, while the effects of warfarin usually are attributed to blood clotting, other pathways deserve consideration. The genes considered as relevant to warfarin dosing, currently funded by ~38 NIH proposals, likely are insufficient to describe warfarin action fully.